Time-Series InSAR Technology for Ascending and Descending Orbital Images to Monitor Surface Deformation of the Metro Network in Chengdu

Abstract

Over the past decade, Chengdu has become one of the fastest growing urban centers in China. However, the massive expansion of the infrastructure and the transportation network has resulted in surface subsidence which typically presents as a hard to detect geological hazard. As an all-day, all-weather, highprecision, and wide-range surface deformation monitoring tool, interferometric synthetic aperture radar (InSAR) technology has unique advantages with respect to monitoring long-period surface subsidence. In this paper, the Sentinel satellite data from March 2018 to March 2021 for the ascending and descending orbits are used to obtain the deformation fields of Chengdu's surface in two different satellite line of sight directions using the time-series InSAR technique. The results are then used to invert the surface deformation field in the vertical direction and analyze it via the Peck and Logistic models. In addition, wavelet transform (WT) technology was used to investigate the relationship between deformation and climate. The results show that the surface deformation in Chengdu is stable, and the rate of deformation in the center of the urban area is within 5 mm/year. The main reason for the emergence of ground settlement funnels is the construction of subways and real estate development. It was also observed that the deformation of the buildings shows a clear periodic pattern, which is closely related to the seasonal rainfall and temperature in Chengdu.

Understanding the Ground Vertical Displacement of Joshimath through Insar Data Processing

“…Interferograms acquired using ASF HyP3 were processed using MintPy (6) to get the desired results. SAR satellites observe obliquely downward not directly below; hence the ascending orbit indicates the observation from west direction and descending orbit indicates the observation from east direction (7). The displacement is calculated by counting the number of fringes in the resultant interferogram and multiplying it with the half wavelength of the SAR (the wavelength of SAR C-band is 5.54 cm).…”

“…We used publicly available data. The Sentinel-1 SAR data is available and can be processed through ASF HyP3 (7). MintPy, which was used to acquire the time series is also publicly available (6).…”

Understanding the Spatial-Temporal Characteristics of Land Subsidence in Shenzhen under Rapid Urbanization Based on MT-InSAR

“…To generate the connection between the ground load and land subsidence, Chen et al [33] and Zhou et al [34] used the building IBI index and machine learning techniques to analyze the relationship between land subsidence and causes, such as static and dynamic load, groundwater level, and sediment thickness. In addition, other factors, including groundwater extraction, building construction, geological strata difference, and seasonal precipitation, can also contribute to urban land subsidence [35][36][37][38]. In Pisa, Italy, Lorenzo Solari et al studied the connection between land subsidence and the age of buildings [39].…”